COMMERCIAL USE
Collection
7 items • Updated • 1
How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf adamksn/Garten2-7B-GGUF:# Run inference directly in the terminal:
llama cli -hf adamksn/Garten2-7B-GGUF:Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf adamksn/Garten2-7B-GGUF:# Run inference directly in the terminal:
./llama-cli -hf adamksn/Garten2-7B-GGUF:Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf adamksn/Garten2-7B-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf adamksn/Garten2-7B-GGUF:Use Docker
docker model run hf.co/adamksn/Garten2-7B-GGUF:Quick Links
Garten2-7B-GGUF
Description
This repo contains GGUF format model files for Garten2-7B-GGUF.
Files Provided
| Name | Quant | Bits | File Size | Remark |
|---|---|---|---|---|
| garten2-7b.IQ3_XXS.gguf | IQ3_XXS | 3 | 3.02 GB | 3.06 bpw quantization |
| garten2-7b.IQ3_S.gguf | IQ3_S | 3 | 3.18 GB | 3.44 bpw quantization |
| garten2-7b.IQ3_M.gguf | IQ3_M | 3 | 3.28 GB | 3.66 bpw quantization mix |
| garten2-7b.Q4_0.gguf | Q4_0 | 4 | 4.11 GB | 3.56G, +0.2166 ppl |
| garten2-7b.IQ4_NL.gguf | IQ4_NL | 4 | 4.16 GB | 4.25 bpw non-linear quantization |
| garten2-7b.Q4_K_M.gguf | Q4_K_M | 4 | 4.37 GB | 3.80G, +0.0532 ppl |
| garten2-7b.Q5_K_M.gguf | Q5_K_M | 5 | 5.13 GB | 4.45G, +0.0122 ppl |
| garten2-7b.Q6_K.gguf | Q6_K | 6 | 5.94 GB | 5.15G, +0.0008 ppl |
| garten2-7b.Q8_0.gguf | Q8_0 | 8 | 7.70 GB | 6.70G, +0.0004 ppl |
Parameters
| path | type | architecture | rope_theta | sliding_win | max_pos_embed |
|---|---|---|---|---|---|
| senseable/Garten2-7B | mistral | MistralForCausalLM | 10000.0 | 4096 | 32768 |
Benchmarks
Original Model Card
Details
Introducing Garten2-7B, a cutting-edge, small 7B all-purpose Language Model (LLM), designed to redefine the boundaries of artificial intelligence in natural language understanding and generation. Garten2-7B stands out with its unique architecture, expertly crafted to deliver exceptional performance in a wide array of tasks, from conversation to content creation.
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Model tree for adamksn/Garten2-7B-GGUF
Base model
mistralai/Mistral-7B-v0.1
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf adamksn/Garten2-7B-GGUF:# Run inference directly in the terminal: llama cli -hf adamksn/Garten2-7B-GGUF: